Image compression is widely used to minimize the space required to store images. Whereas the known image compression methodologies are optimized in view of storage requirements resources required to uncompress/decode compressed images are considered of marginal concern. Image compression methodologies having high compression ratios are typically processing and bandwidth demanding. In particular processing systems with limited capabilities which would benefit from the reduced storage space demand due to high compression ratios are often not capable to provide the required processing and bandwidth capabilities.
In the state of the art, approaches are known to leverage specific or dedicated hardware solutions for uncompressing/decoding compressed images. For instance, the use of OpenCL kernels applicable with a large number of today's graphics processing subsystem is suggested; cf. for instance “http://developer.amd.com/resources/documentation-articles/articles-whitepapers/jpeg-decoding-with-run-length-encoding-a-cpu-and-gpu-approach!”. This approach reduces the requirement of processing resources provided by a general purpose processor in that functionalities of a graphics processing subsystem are employed but does still involves high bandwidth consumption between memory and graphics processing subsystem.
The consideration applies to dedicated hardware solutions, which also reduces the requirement of processing resources provided by a general purpose processor but disregard the bandwidth consumption due to data transfers from and to memory.